SUP-TESTS FOR LINEARITY IN A GENERAL NONLINEAR AR(1) MODEL
From MaRDI portal
Publication:3580631
DOI10.1017/S0266466609990430zbMath1294.62200OpenAlexW2172097605MaRDI QIDQ3580631
Lajos Horváth, Jean-Michel Zakoian, Christian Francq
Publication date: 13 August 2010
Published in: Econometric Theory (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1017/s0266466609990430
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Extreme value theory; extremal stochastic processes (60G70) General nonlinear regression (62J02) Functional limit theorems; invariance principles (60F17) Non-Markovian processes: hypothesis testing (62M07)
Related Items (8)
Testing for parameter stability in nonlinear autoregressive models ⋮ Adjusted Supremum Score-Type Statistics for Evaluating Non-Standard Hypotheses ⋮ Goodness-of-fit tests for Log-GARCH and EGARCH models ⋮ Estimation and testing linearity for non-linear mixed Poisson autoregressions ⋮ Testing Linearity for Network Autoregressive Models ⋮ Tests for Linearity in Star Models: Supwald and Lm-Type Tests ⋮ Quantile Regression for Location‐Scale Time Series Models with Conditional Heteroscedasticity ⋮ TESTING AND INFERENCE IN NONLINEAR COINTEGRATING VECTOR ERROR CORRECTION MODELS
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Likelihood-based inference with singular information matrix
- Specification testing when score test statistics are identically zero
- Admissibility of the likelihood ratio test when a nuisance parameter is present only under the alternative
- Tests for Parameter Instability and Structural Change With Unknown Change Point
- Non-linear time series and Markov chains
- CONSISTENT SPECIFICATION TESTING WITH NUISANCE PARAMETERS PRESENT ONLY UNDER THE ALTERNATIVE
- Testing for Neglected Heterogeneity
- ON ESTIMATING THRESHOLDS IN AUTOREGRESSIVE MODELS
- Testing linearity against smooth transition autoregressive models
- Modelling nonlinear random vibrations using an amplitude-dependent autoregressive time series model
- Hypothesis Testing When a Nuisance Parameter is Present Only Under the Alternative
- A Uniform Law of Large Numbers for Dependent and Heterogeneous Data Processes
- Optimal Tests when a Nuisance Parameter is Present Only Under the Alternative
- The Lindeberg-Levy Theorem for Martingales
- Inference When a Nuisance Parameter Is Not Identified Under the Null Hypothesis
This page was built for publication: SUP-TESTS FOR LINEARITY IN A GENERAL NONLINEAR AR(1) MODEL
